Multi-Cloud DevOps with Generative AI Training
This advanced training program provides learners with hands-on expertise in multi-cloud DevOps engineering combined with Generative AI automation. It covers infrastructure automation, CI/CD pipelines, Kubernetes orchestration, AI integration, and modern MLOps workflows—empowering engineers to design, deploy, and manage intelligent, automated, multi-cloud environments
COURSE HIGHLIGHTS
- 40 Hours of Live Online Sessions
- Learn from Industry Experts
- Real-time Industry Cases Study
- Access to Recorded Sessions
- Hands-On Logging, Monitoring, Responding
- Extended Post Training Support
- Personalized Doubt Sessions
- Expert Career Services to Help You Land a Job
Tools Coverd
Course Description
Key Features
The Multi-Cloud DevOps with Generative AI program is designed for IT professionals, developers, and cloud engineers who want to master the next generation of DevOps workflows.
You’ll learn how to:
Build and manage applications across multiple cloud environments
Use AI-driven tools to accelerate deployment, monitoring, and optimization
Integrate Generative AI models into DevOps pipelines for intelligent automation
Implement CI/CD, IaC (Infrastructure as Code), and AIOps across platforms
The world of cloud computing is rapidly evolving, and organizations today demand professionals who can work seamlessly across multiple cloud platforms while leveraging the power of artificial intelligence to automate, optimize, and innovate. The Multi-Cloud DevOps with Generative AI Training is designed precisely for this new era of intelligent cloud operations — blending the depth of DevOps with the innovation of Generative AI to create highly capable, future-ready professionals.
This training goes far beyond traditional DevOps. It helps you master deployment and automation across AWS, Azure, and Google Cloud, while integrating Generative AI tools to enhance every stage of the DevOps lifecycle — from code generation and CI/CD optimization to predictive monitoring and automated troubleshooting. You will learn how AI can streamline workflows, reduce manual effort, and empower development teams to move from reactive to proactive operations.
The course is led by industry-certified experts who bring real-world experience from working with leading organizations in cloud infrastructure and AI automation. Through immersive hands-on projects, you’ll not only understand core multi-cloud and DevOps concepts but also apply them in real scenarios — building pipelines, deploying scalable cloud applications, and using AI-powered assistants to analyze performance, optimize costs, and manage infrastructure efficiently.
What Will You Learn?
- By the end of the Multi-Cloud DevOps with Generative AI Training, you will be able to:
- Master Multi-Cloud Architecture: Understand and work across AWS, Azure, and Google Cloud platforms to design, deploy, and manage scalable cloud solutions.
- Implement DevOps Pipelines: Build end-to-end CI/CD pipelines using tools like Jenkins, GitHub Actions, and GitLab for faster and more reliable delivery.
- Automate Infrastructure with IaC: Use Terraform and Ansible to automate provisioning, configuration, and infrastructure management across multiple clouds.
- Containerize and Orchestrate Applications: Deploy and manage applications using Docker and Kubernetes with best practices in scaling and monitoring.
- Integrate Generative AI into DevOps: Learn how AI tools like ChatGPT, LangChain, and OpenAI APIs can automate coding, testing, and deployment tasks.
- Leverage AIOps for Smart Monitoring: Apply AI-driven insights for predictive maintenance, log analysis, anomaly detection, and real-time system optimization.
- Enhance Collaboration and Productivity: Use intelligent assistants to streamline communication, automate documentation, and optimize workflow efficiency.
- Build AI-Powered ChatOps Tools: Create conversational bots that monitor pipelines, track performance, and respond to DevOps alerts automatically.
- Optimize Cloud Costs with AI: Utilize machine learning and analytics to forecast usage, reduce resource wastage, and manage multi-cloud budgets effectively.
Pre-requisites
- Before enrolling in the Multi-Cloud DevOps with Generative AI Training, learners are expected to have a basic understanding of IT systems and a strong enthusiasm for automation, cloud technologies, and AI. While no advanced experience is required, the following foundational skills and knowledge will help you get the most out of the program:
- Basic Cloud Knowledge: Familiarity with any one cloud platform (AWS, Azure, or Google Cloud) and general concepts like servers, storage, and networking.
- Fundamentals of Linux & Command Line: Comfort with basic Linux commands and environment navigation for cloud and DevOps tasks.
- Programming Essentials: Basic understanding of scripting or programming languages such as Python, Bash, or Shell scripting.
- Understanding of Software Development: Awareness of the software development lifecycle (SDLC) and version control using Git/GitHub.
- Analytical Mindset: Interest in automation, problem-solving, and integrating intelligent systems into workflows.
Who Can Join This Course?
- The following types of candidates can join this certification course –
- Cloud Engineers & Administrators
- DevOps Professionals
- Software Developers & Programmers
- System Administrators & IT Operations Teams
- AI & Machine Learning Enthusiasts
- Students & Fresh Graduates (Tech Background)
- Technology Consultants & Solution Architects
Our Distinctness
However, our course is open to any candidate who has an understanding and eagerness to Learn Multi-Cloud DevOps with Generative AI Training
Avail the benefits of our Multi-Cloud DevOps with Generative AI Training library and highly effective resources. We go beyond the objective of obtaining a certificate and promote your excellence in designing, planning, and scaling AWS implementations across 70+ cloud computing services.
Course Module
Want the Full Course Syllabus?
These are just the highlights! Get the complete, detailed course syllabus including all modules, timelines, and bonus materials.
GET A FREE DEMO CLASS
Understand DevOps fundamentals, the multi-cloud landscape, and how cloudenvironments integrate with modern DevOps workflows
- Understanding DevOps culture, lifecycle, and benefits
- Cloud computing overview — AWS, Azure, and GCP
- Multi-cloud strategy, interoperability, and governance
- Setting up accounts and CLI access for AWS, Azure, and GCP
- Hands-on: Configure and connect multi-cloud environments
Learn source control and collaborative workflows essential for DevOps automation.
- Git fundamentals: branching, merging, and versioning
- GitHub, GitLab, and Bitbucket integration
- CI/CD overview and source control best practices
- Hands-on: Create a multi-cloud project repository with GitHub Actions
Build automated pipelines to deliver applications efficiently across multiple cloud platforms.
- Designing CI/CD pipelines across AWS, Azure, and GCP
- Jenkins, GitHub Actions, and Azure DevOps setup
- Automating build, test, and deploy processes
- Hands-on: Deploy a sample web app using Jenkins on AWS and Azure
Master container-based application deployment across multiple cloud Kubernetes clusters.
- Docker deep dive — images, containers, networks
- Kubernetes architecture — Pods, Deployments, Services, Ingress
- Multi-cloud orchestration with AKS (Azure), EKS (AWS), and GKE (Google)
- Hands-on: Deploy a microservice across AKS and EKS clusters
Automate multi-cloud provisioning using declarative infrastructure management.
- Terraform fundamentals for AWS, Azure, and GCP
- Creating reusable Terraform modules
- Managing Terraform state and environments
- Hands-on: Provision infrastructure simultaneously in AWS and Azure
Learn configuration automation and dynamic infrastructure setup using scripting and orchestration tools.
- Ansible fundamentals and YAML-based playbooks
- Integrating Ansible with Terraform for automation
- Cloud automation using Python & Boto3
- Hands-on: Deploy and configure servers automatically using Ansible Playbooks
Implement secure, monitored, and compliant DevOps pipelines.
- Monitoring tools: Prometheus, Grafana, CloudWatch, Azure Monitor
- Security scanning tools: Snyk, Trivy, Aqua Security
- Building secure CI/CD pipelines with automated checks
- Building secure CI/CD pipelines with automated checks
Integrate Generative AI tools into DevOps to enhance productivity, automation, and intelligence.
- Introduction to AI/ML and Generative AI concepts
- Using GitHub Copilot and ChatGPT for DevOps scripting & documentation
- Understanding LLMs (OpenAI, Azure OpenAI, Gemini)
- AI frameworks: LangChain, LlamaIndex, Hugging Face
- Build an AI agent that monitors deployments and suggests fixes
- Use AI to generate Jenkins pipelines and debug errors
- Implement AI-driven incident management using Azure OpenAI
Explore how AI enhances observability, automation, and decision-making in DevOps
- Overview of AIOps and MLOps concepts
- AI-assisted performance optimization
- Predictive failure detection using AI on logs
- Building AI assistants for cloud operations
- Hands-on: Use AI models to predict server or pipeline failures
Combine all learned concepts to deploy and monitor a production-grade, AI-assisted, multi-cloud application
- End-to-end multi-cloud CI/CD + IaC + Kubernetes deployment
- Implementing real-time monitoring and alerting
- AI-based change management and release automation
- Hands-on Project: Deploy a full-stack application with AI-driven automation across
- AWS, Azure, and GCP
Showcase complete mastery by implementing and defending a real-world AI-Driven DevOps pipeline.
- Final Capstone: AI-assisted DevOps automation for multi-cloud infrastructure
- Peer review and project defense
- Resume building and LinkedIn optimization for DevOps & Cloud roles
- Future of AI in DevOps — AIOps, FinOps, and AI-powered SRE
Benefits of Having Multi-Cloud DevOps with Generative AI Training Certification
- Expanded Job Opportunities: Opens doors to roles such as DevOps Engineer, Cloud Engineer, Site Reliability Engineer (SRE), MLOps Engineer, and AI Platform Engineer across multiple industries.
- Higher Salary Potential: Certified professionals often command higher compensation due to expertise in both multi-cloud platforms and Generative AI integration.
- Future-Proof Career Path: Combines in-demand skills in cloud computing, DevOps automation, and Generative AI, ensuring long-term career relevance.
- Global Employability: Multi-cloud knowledge (AWS, Azure, GCP) makes you suitable for international projects and global organizations.
- Leadership & Advanced Roles: Positions you for senior roles like DevOps Architect, Cloud Solutions Architect, or AI Infrastructure Lead.
- Competitive Advantage: Differentiates your profile in a crowded job market by showcasing advanced, cross-domain expertise.
- Multi-Cloud Expertise: Enables seamless deployment, management, and optimization of applications across multiple cloud providers.
- Improved Automation & Efficiency: Leverages Generative AI to automate CI/CD pipelines, infrastructure provisioning, and incident resolution.
- Enhanced Problem-Solving Skills: AI-driven insights help predict failures, optimize performance, and improve system reliability.
- Faster Development Cycles: Accelerates application delivery through intelligent testing, monitoring, and deployment strategies.
- Scalable & Secure Systems: Builds resilient, cost-efficient, and secure cloud-native architectures.
- Innovation Enablement: Empowers professionals to integrate AI-driven solutions into DevOps workflows, fostering continuous innovation.
- Cross-Team Collaboration: Improves collaboration between development, operations, and AI teams using unified, intelligent DevOps practices.
Key Features
Cloud Platform Training
Work with AWS, Azure, and GCP environments.
Real-World Projects
Build and deploy enterprise-grade applications.
Lifetime Access
Access updated content and resources anytime.
Industry Certification
Earn a recognized DevOps certification
AI-Powered Automation
Integrate Generative AI into DevOps tasks.
Career Assistance
Get guidance for resume building and job placement.
Expert Mentorship
Learn from certified industry professionals
CI/CD Pipelines
Automate build, test, and deployment processes.
Choose Your Preferred Learning Mode
Our inspiring and updated training program design will accelerate your career advancement –
1-TO-1 TRAINING
Customized schedule, learn at your dedicated hour with instant doubt clarification and guaranteed sessions.
ONLINE TRAINING
Flexibility, convenience, and time-saving; more effective learning with
cost savings.
CORPORATE TRAINING
Learn anytime, anywhere, across the globe with customized corporate training. Hire a trainer and progress at your own pace.
Why InsureTech
Experienced Instructors
Post Training Support
Customized Training
Flexible
Schedule
Access to Recorded Sessions
Frequently asked question
This certification equips you with in-demand skills in multi-cloud management, DevOps automation, and Generative AI integration. It helps you master real-world tools like AWS, Azure, GCP, Docker, and Jenkins while applying AI to streamline workflows. By the end of the course, you’ll earn a recognized credential, gain hands-on project experience, and become job-ready for high-growth roles in cloud and AI-driven DevOps.
You can opt for different types of jobs relating to Multi-Cloud DevOps Engineer
Yes, contact our support team to book a seat for the demo lecture.
Yes, but you need to prepare yourself to kick-start your career.
You will receive comprehensive support during and even after completing your course.
Yes, Multi-Cloud DevOps with Generative AI training is generally worth it because it combines three high-demand skill areas—cloud engineering, automation, and AI-driven workflows—making you more competitive in a rapidly evolving tech market, improving your ability to automate tasks, optimize infrastructure, and deliver faster, more reliable software, though its value depends on your existing skill level, career goals, and whether your target companies are adopting AI-driven DevOps practices.
Multi-Cloud DevOps specialists are responsible for designing, automating, securing, and optimizing applications across multiple cloud platforms like AWS, Azure, and GCP; they build and manage CI/CD pipelines, use Infrastructure as Code to standardize deployments, ensure security and compliance across clouds, implement monitoring and observability systems, manage containerized environments like Kubernetes, optimize cloud costs, and create resilient architectures with high availability and disaster recovery to support smooth, efficient, and scalable multi-cloud operations.
To become a Multi-Cloud DevOps specialist, you need strong skills in cloud platforms like AWS, Azure, and GCP, along with proficiency in CI/CD tools such as Jenkins, GitLab, or GitHub Actions; expertise in Infrastructure as Code tools like Terraform, CloudFormation, or Ansible; solid understanding of containerization and orchestration using Docker and Kubernetes; knowledge of monitoring and observability tools such as Prometheus, Grafana, CloudWatch, and Azure Monitor; strong Linux and scripting skills (Bash, Python); familiarity with networking, security, and identity management across multiple clouds; experience with automation, configuration management, and version control using Git; and the ability to troubleshoot distributed systems while ensuring scalability, reliability, and cost optimization across cloud environments.
Yes — the course can be fully customized to meet your organization’s specific needs. Whether your team operates in AWS, Azure, Google Cloud, or a multi-cloud environment, the training can be tailored to align with your security goals, industry standards, and team skill levels.
Yes — we offer special group discounts for organizations or teams enrolling multiple participants in the course. Group pricing helps make professional cloud security training more affordable while enabling teams to learn together and apply consistent best practices across the organization.
The Multi-Cloud DevOps with Generative AI Training certification positions you at the forefront of the tech industry by combining two of the most sought-after skill sets — cloud automation and artificial intelligence integration. It validates your ability to manage complex, multi-cloud infrastructures while leveraging AI tools to optimize performance, automate workflows, and improve system reliability.
Holding this certification demonstrates that you have mastered multi-cloud management, DevOps automation, and Generative AI integration—a rare and highly valued combination in today’s tech industry. It validates your ability to build, deploy, and optimize applications across AWS, Azure, and Google Cloud, while using AI tools to streamline workflows, predict issues, and enhance performance.
